Jan Tomsa

PM by day, maker by night.

[Jan Tomsa @DetektivTomy]

@setupspawn Is it still a rickroll if you know what happens? 😀
Clicked anyway, I just like that song 😄

[Jan Tomsa @DetektivTomy]

@MrReitz @BojackBujin @kataikou @OrevaZSN Claude Opus 5 about CSS DVD protection system

[Jan Tomsa @DetektivTomy]

@PieterBolleke @stevekrouse If I understand right, you can always use the key.

[Jan Tomsa @DetektivTomy]

@GamerLadka @DudespostingWs More like more than 3.5 minutes.

[Jan Tomsa @DetektivTomy]

@TotherAlistair I am quite new to Claude Code (GH Copilot before) and recently I noticed that after describing proposed next step it offers (in gray text in prompt line) something like "proceed with the changes" or "go for it". So much energy saved when I only need to press tab+enter 🙂

[Jan Tomsa @DetektivTomy]

@bezicicestinar Jeden z důvodů, proč už léta nečtu překlady, nýbrž originály.
Druhý důvod: nemusím si lámat hlavu tím, jaká byla autorova původní myšlenka , než prošla tím patlalským překladem.

[Liberty Pill Memes @LibertyPillMeme]

"Wish servers" 💀

[Jan Tomsa @DetektivTomy]

@lauriewired @davepl1968 And that's just the building. If you take into account all the PiL and HiL testing, you better have a cabinet full of HW that you bought while you could, if you thought well ahead.

[Jan Tomsa @DetektivTomy]

@lauriewired @davepl1968 In automotive the manufacturer is obligated to be able to provide bugfixes at least 15 years after End of production, while the SW is developed ~4 years before Start of production. In my work we were seriously discussing how to build the SWC in 2050. A lot of hope goes to VMs tbh

[Jan Tomsa @DetektivTomy]

@sanitak_pisarik Asi bych byl v pokušení dopomoci mu k tomu, aby to jeho hlášení - úporná bolest kolene po údajném úrazu - bylo pravdivé.

[Jan Tomsa @DetektivTomy]

@PetrLazecky1 @DavidGrudl Takový Simon Willison z Wishe 🙂

[Jan Tomsa @DetektivTomy]

Piece of art. To me it resembles the works of @Amanita_Design

[Tommi @tommithetechie]

This gorgeous machine is the AKAT-1. Constructed in Poland in 1959 by Jacek Karpinski and Janusz Tomaszewski, this was one of the world's first transistor-based analog computers.

If you think the AKAT-1 looks more like a piece of modern art than a computer, you're onto something. The exterior and control panel were actually designed by artists associated with the Warsaw Academy of Fine Arts.

Sadly, this machine never actually went into mass production, but don't you wish it had?

#RetroTech #VintageComputing #ComputerHistory

[Kirill Skrygan @kskrygan]

Would you be interested if JetBrains releases a totally local AI agent, working 100% on your laptop, using our code insight engine and deeply integrated into the IDE?

Yes, it will be probably 1 month behind the very recent frontier models, but no token blood bath anymore

WDYT?

[Darren Shepherd @ibuildthecloud]

Seriously @Microsoft stop doing this crap. "Confirm" or "Set later". Why isn't there a no? Can't you respect my choice? Why can't you respect me as a user? I'm sick of being treated as an ad channel. I paid for your product.

[Hedgie @HedgieMarkets]

🦔A researcher invented a fake eye condition called bixonimania, uploaded two obviously fraudulent papers about it to an academic server, and watched major AI systems present it as real medicine within weeks.
The fake papers thanked Starfleet Academy, cited funding from the Professor Sideshow Bob Foundation and the University of Fellowship of the Ring, and stated mid-paper that the entire thing was made up. Google's Gemini told users it was caused by blue light. Perplexity cited its prevalence at one in 90,000 people.

ChatGPT advised users whether their symptoms matched. The fake research was then cited in a peer-reviewed journal that only retracted it after Nature contacted the publisher.

My Take
The researcher made the papers as obviously fake as possible on purpose. The AI systems didn't catch it. Neither did the human researchers who cited it in real journals, which means people are feeding AI-generated references into their work without reading what they're actually citing.

I've covered the FDA using AI for drug review, the NYC hospital CEO ready to replace radiologists, and ChatGPT Health launching this year. All of that is happening in the same environment where a condition funded by a Simpsons character and endorsed by the crew of the Enterprise was being presented as emerging medical consensus. The people making these deployment decisions seem to believe the pipeline from research to AI to patient is more supervised than it actually is. This experiment suggests it isn't supervised much at all.

Hedgie🤗
https://t.co/8Kg8FOrgHW

[Curiosity @CuriosityonX]

【Breaking 🚨】 Curiosity wheels taken yesterday, showing the damages caused during the 13 years it has been on the Red Planet

[Jan Tomsa @DetektivTomy]

@adent Za mě největší game changer je closed-loop code generation. Jakmile má agent možnost po každém kroku řešení otestovat, dokáže skoro vždy autonomně doiterovat do cíle.

[Lukas Ziegler @lukas_m_ziegler]

High school students built an autonomous ball-collecting robot! 🎾

A group of high school students built a robot that picks up balls and shoots them into a bin while moving without stopping, with impressive speed and accuracy.

It combines mechanical design, sensors, and software making constant adjustments in real time while the robot is driving.

When teenagers can build systems this sophisticated, the talent pipeline for the robotics industry is accelerating!
~~

♻️ Join the weekly robotics newsletter, and never miss any news → https://t.co/GoA3ZuwoPB

[kanav @kanavtwt]

Someone built a Google translate for Linkedin 😭

[Mark Gadala-Maria @markgadala]

This is wild.

143 million people thought they were catching Pokémon. They were actually building one of the largest real-world visual datasets in AI history.

Niantic just disclosed that photos and AR scans collected through Pokémon Go have produced a dataset of over 30 billion real-world images. The company is now using that data to power visual navigation AI for delivery robots.

Players didn't just walk around with their phones. They scanned landmarks, storefronts, parks, and sidewalks from every angle, at every time of day, in lighting and weather conditions that staged photography would never capture. They documented the physical world at a scale no mapping company with a fleet of vehicles could have replicated on the same timeline or budget.

Niantic collected this systematically, data point by data point, across eight years, while users thought the only thing at stake was catching a rare Charizard.

The most valuable AI training datasets in the world aren't being assembled in data centers. They're being built by people who have no idea they're building them.